ABSTRACT
Grid
computing is a collection of computer resources from multiple locations
assembled to provide computational services, storage, data or application
services. Grid computing users gain access to computing resources with little
or no knowledge of where those resources are located or what the underlying
technologies, hardware, operating system, and so on are. Reliability and
performance are among the key challenges to deal with in grid computing
environments. Accordingly, grid scheduling algorithms have been proposed to
reduce the likelihood of resource failure and to reduce the overhead of
recovering from resource failure. Check pointing is one of the fault tolerance
techniques when resources fail. This technique reduces the work lost due to
resource faults but can introduce significant runtime overhead. This research
provided an enhancd check pointing technique that extends a recent research and
aims at lowering the runtime overhead of checkpoints. The results of the
simulation using GridSim showed that keeping the number of resources constant
and varying the number of gridlets, improvements of up to 9%, 11%, and 11% on
throughput, make span and turnaround time, respectively, were achieved while
varying the number of resources and keeping the number of gridlets constant,
improvements of up to 8%, 11%, and 9% on throughput, make span and turnaround
time, respectively, were achieved. These results indicate the potential
usefulness of our research contribution to applications in practical grid
computing environments.
CHAPTER ONE
INTRODUCTION
1.1 Background of the
Study
Grid
computing uses a computer network in which each computer's resources are shared
with every other computer in the system. In view of this, computing becomes
pervasive and individual users (or client applications) gain access to
computing resources (processors, storage, data, applications, and so on) as
needed with little or no knowledge of where those resources are located or what
the underlying technologies, hardware, operating system, and so on are. The
main objective in grid scheduling is to finish a job or application as soon as
possible (Harshadkumar and Vipul, 2014). Fault tolerance is an important
property for large scale computational grid systems, where geographically
distributed nodes cooperate to execute a task in order to achieve a high level
of reliability and availability. A common approach to guarantee an acceptable
level of fault tolerance in scientific computing is to use checkpointing. When
a task fails it can be restarted from its most recently checkpointed state
rather than from the beginning, which reduces the system loss and ensures
reliability (Bakhta and Ghalem, 2014).
1.2 Motivation
The
ability to checkpoint a running application and restart it later can provide
many useful benefits like fault recovery, advanced resource sharing, dynamic
load balancing and improved service availability. A fault-tolerant service is
essential to satisfy QoS requirements in grid computing. However, excessive
checkpointing results in performance degradation. Thus there is the need to
improve the performance by reducing the number of times that checkpointing is
invoked.
TOPIC: DEVELOPMENT OF AN ENHANCED CHECK POINTING TECHNIQUE IN GRID COMPUTING USING PROGRAMMER LEVEL CONTROLS
Format: MS Word
Chapters: 1 - 5
Delivery: Email
Delivery: Email
Number of Pages: 65
Price: 3000 NGN
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